Fair, effective, efficient and differentiated scheduling in an enterprise data warehouse
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Requirement-based query and update scheduling in real-time data warehouses
WAIM'11 Proceedings of the 12th international conference on Web-age information management
Workload management: a technology perspective with respect to self-* characteristics
Artificial Intelligence Review
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A typical online Business Intelligence (BI) workload consists of a combination of short, less intensive queries, along with long, resource intensive queries. As such, the longest queries in a typical BI workload may take several orders of magnitude more time to execute, compared with the shortest queries in the workload. This makes it challenging to design a good Mixed Workload Scheduler (MWS). In this paper we first define the design criteria that make a 'good' MWS. We then use these criteria to design rFEED, a MWS that is fair, effective, efficient, and differentiated. We simulate real workloads and compare our rFEED MWS with models of the current best of breed commercial systems. We show that the rFEED MWS works extremely well.